Literature DB >> 27346902

Generalized LASSO with under-determined regularization matrices.

Junbo Duan1, Charles Soussen2, David Brie2, Jérôme Idier3, Mingxi Wan1, Yu-Ping Wang4.   

Abstract

This paper studies the intrinsic connection between a generalized LASSO and a basic LASSO formulation. The former is the extended version of the latter by introducing a regularization matrix to the coefficients. We show that when the regularization matrix is even- or under-determined with full rank conditions, the generalized LASSO can be transformed into the LASSO form via the Lagrangian framework. In addition, we show that some published results of LASSO can be extended to the generalized LASSO, and some variants of LASSO, e.g., robust LASSO, can be rewritten into the generalized LASSO form and hence can be transformed into basic LASSO. Based on this connection, many existing results concerning LASSO, e.g., efficient LASSO solvers, can be used for generalized LASSO.

Entities:  

Keywords:  LASSO; deconvolution; diagonally dominant; generalized LASSO; robust LASSO; solution path; total variation

Year:  2016        PMID: 27346902      PMCID: PMC4917299          DOI: 10.1016/j.sigpro.2016.03.001

Source DB:  PubMed          Journal:  Signal Processing        ISSN: 0165-1684            Impact factor:   4.662


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